Two important components of the baseband signal processing of advanced wire-free communications systems such as the third generation mobile radio systems (3G systems) are the transmission-end channel coding and the reception-end channel decoding. In the case of systems based on the 3GPP standard (3GPP—3rd Generation Partnership Project) technically demanding channel coding methods are used, based on convolution coding and on turbocoding. Turbocodes in particular offer excellent resistance to interference, in which a bit error rate which is still sufficiently low can be achieved at considerably lower transmission power levels, or a considerably lower bit error rate at a higher transmission power level, can be achieved than with other channel coding methods.
The complexity of the coder is in this case fundamentally negligible in comparison to the complexity of the decoder. Decoders such as these generally operate using so-called trellis-based algorithms, which include the Viterbi algorithm, the maximum a posteriori algorithm (MAP) and the soft output Viterbi algorithm (SOVA).
Turbodecoders typically use two soft input/soft output decoder elements (SISO decoders), between which information is interchanged, with the sought decoded value being determined iteratively. The decoder elements use either the MAP algorithm or the SOVA. In contrast to the situation with the turbodecoder, a decoder using convolutional codes does not necessarily need to have an SISO decoder; a simple Viterbi algorithm without a soft output or else the MAP algorithm is thus frequently used for decoding of convolutional codes.
Owing to the complexity of such decoding methods, base-band circuits whose power consumption, surface area and data throughput are designed to be particularly efficient are required in order to produce convenient mobile appliances with low power losses. This necessitates solutions with a high degree of flexibility so that, in particular, different channel coding methods and channel decoding methods for one or more Standards (for example UMTS and GSM) can be implemented using common hardware. Purely software-based solutions using standard processors in principle ensure a high degree of flexibility, but they have weaknesses in terms of the data throughput rate and the power losses. Alternative solutions using dedicated hardware, which allow a high data throughput rate with comparatively low power losses, fundamentally have the disadvantage that the hardware cannot be used as flexibly.